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Currently it supports following detectors in onnx runtime. It works with minimal dependencies. It is designed in such a manner to run on edge devices also.\n\n--------------------\n### Object Detection:\n| Detector | onnx |\n|--|--|\n| [yolov5](https://github.com/ultralytics/yolov5) | ✅| \n| [yolov6](https://github.com/meituan/YOLOv6) | ✅ |\n| [yolov7](https://github.com/WongKinYiu/yolov7) | ✅ | \n| [yolov8](https://github.com/ultralytics/ultralytics) | ✅ | \n| [yolov5u](https://github.com/ultralytics/ultralytics) | ✅ |\n| [yoloX](https://github.com/Megvii-BaseDetection/YOLOX) | ✅ |\n| [Damo-yolo](https://github.com/tinyvision/DAMO-YOLO) | ✅ |\n\n--------------------\n### Instance Segmentation:\n\n| Detector Name | onnx |\n|--|--|\n| [yolov5](https://github.com/ultralytics/yolov5) | ✅ |\n| [yolov7](https://github.com/WongKinYiu/yolov7) | #TODO |  \n| [yolov8](https://github.com/ultralytics/ultralytics) | ✅ |  \n\n\n--------------------\n### Multi Object Tracker:\n\n| Tracker Name | Integration |\n|--|--|\n| [SORT](https://github.com/ultralytics/yolov5) | ✅ |\n| [ByteTrack](https://github.com/WongKinYiu/yolov7) | ✅ |\n| [OcSort](https://github.com/ultralytics/ultralytics) | ✅ |\n| [Norfair](https://github.com/ultralytics/ultralytics) | - |\n\n--------------------\n### Installation:\n\nInstallation can be done via pip using following argument\n```\n pip3 install git+https://github.com/hardikdava/EyeQ.git\n```\n--------------------\n#### TODO:\n- Docker support\n- RestAPI server ✅\n- Multi object trackers ✅\n- Instance segmentation ✅\n- Yolo Dataset loading ✅\n- COCO dataset loading\n- Object detection evaluation ✅\n- Multi object tracker evaluation ✅\n- Automatic annotation support using clip, grounding dino and sam\n- Introduce SAHI technique\n\n#### Available APIs:\n\n- Object Detection Inference using ONNX runtime\n- Object Detction Evaluation API\n- Model serving using RESTAPI using FastAPI based server\n- Multi object Tracking for bounding boxes\n- Multi object Tracking\n- Instance segmentation support\n- Data loading for yolo\n\nNote: models are trained using [notebooks](https://github.com/roboflow/notebooks) prepared by roboflow but models are not included with codebase.\n\n### References:\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhardikdava%2Feyeq","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhardikdava%2Feyeq","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhardikdava%2Feyeq/lists"}